Influential Software Package

Identification, Classification and Prioritization of the Most Influential Nodes.

IVI: An Algorithm for Capturing Influencers

The IVI shiny app for the identification and visualization of the most influential nodes within networks.

IVI (Integrated Value of Influence) is an algorithm that identifies the most influential network nodes by capturing all the topological dimensions of the network and integrating the hubness and spreading values of nodes.


ExIR: An Elixir for Biologists

The ExIR shiny app for the for classification, ranking, and visualization of top candidate features.

ExIR (Experimental-data-based Integrative Ranking) is a versetile, and sophisticated model that could be used for analyzing any type of experimental data (e.g. transcriptomics, proteomics, etc.).


The Influential Software Package

The goal of the Influential Software Package is to help researchers identify the most influential nodes in a network as well as the classification and ranking of top candidate features. All of the features and functions of this software package have been adapted from the R package influential . This web app includes the following shiny apps:


The Integrated Value of Influence (IVI) is a robust and versatile algorithm that captures all topological dimensions of a network for the identification of network most influential nodes. To this end, IVI integrates the most significant network centrality measures in order to synergize their effects and simultaneously remove their biases. The IVI is the first method that truly integrates the effect of six important network centrality measures.


The Experimental data-based Integrative Ranking (ExIR) is a sophisticated model for classification and ranking of the top candidate features (e.g. genes, proteins, and metabolites) based on only the experimental data. You could use any type of experimental data such as transcriptomics, proteomics, etc. to run the ExIR model. Also, you can visualize and computationally validate (knockout/over-express) top candidates proposed by the ExIR.

Influential Software Package Team

Adrian Salavaty

Researcher & Developer

Adrian (Abbas) obtained his B.Sc. and M.Sc. degrees in Molecular Genetics and Biology-Biochemistry, respectively. His Bachelor's project as well as his Master's thesis was purely computational. In this regard, he used both bioinformatics and systems biology approaches to acomplish these projects. He is now a bioinformatician and systems biologist pursuing his Ph.D. at the Australian Regenerative Medicine Institute (ARMI), Monash University.

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Mirana Ramialison


Mirana Ramialison received her Engineering degree from the University of Luminy, France. After obtaining her PhD in Developmental Genomics from the EMBL in Heidelberg, Germany, she joined the Victor Chang Cardiac Research Institute in Sydney as a Post-Doctoral fellow. Then, she moved to Melbourne and established her laboratory at the Australian Regenerative Medicine Institute (ARMI) in 2014 before joining the Murdoch Children's Research Institute in 2020.

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Peter Currie


Peter D. Currie received his PhD in Drosophila genetics from Syracuse University. He undertook postdoctoral training in zebrafish development at the Imperial Cancer Research Fund (now Cancer Research UK) in London, UK.. He has worked as a laboratory head at MRC Human Genetics Unit in Edinburgh and Victor Chang Cardiac Research Institute in Sydney. In 2016 he was appointed Director of Research of the ARMI at Monash University, Melbourne.

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Salavaty A, Ramialison M, Currie PD. Integrated Value of Influence: An Integrative Method for the Identification of the Most Influential Nodes within Networks. Patterns. August 2020.


Ehsan Rezaei-Darzi, MSc Biostatistics, for his consultations regarding proper use of statistical methods and evaluations in the IVI project.

Hieu Tri Nim, PhD, for his constructive feedback on the IVI manuscript.

Lan Nguyen, PhD, for his constructive feedback on the ExIR manuscript.


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